51 citations · 101 across the 6 of their papers we have counts for
6 papers
OPFData: Large-scale datasets for AC optimal power flow with topological perturbations
Sean Lovett, Miha Zgubic, Sofia Liguori +6
Solving the AC optimal power flow problem (AC-OPF) is critical to the efficient and safe planning and operation of power grids. Small efficiency improvements in this domain have th…
The Ethics of Advanced AI Assistants
Iason Gabriel, Arianna Manzini, Geoff Keeling +54
This paper focuses on the opportunities and the ethical and societal risks posed by advanced AI assistants. We define advanced AI assistants as artificial agents with natural langu…
CANOS: A Fast and Scalable Neural AC-OPF Solver Robust To N-1 Perturbations
Luis Piloto, Sofia Liguori, Sephora Madjiheurem +6
Optimal Power Flow (OPF) refers to a wide range of related optimization problems with the goal of operating power systems efficiently and securely. In the simplest setting, OPF det…
Controlling Commercial Cooling Systems Using Reinforcement Learning
Jerry Luo, Cosmin Paduraru, Octavian Voicu +33
This paper is a technical overview of DeepMind and Google's recent work on reinforcement learning for controlling commercial cooling systems. Building on expertise that began with…
Semi-analytical Industrial Cooling System Model for Reinforcement Learning
Yuri Chervonyi, Praneet Dutta, Piotr Trochim +9
We present a hybrid industrial cooling system model that embeds analytical solutions within a multi-physics simulation. This model is designed for reinforcement learning (RL) appli…
On the role of planning in model-based deep reinforcement learning
Jessica B. Hamrick, Abram L. Friesen, Feryal Behbahani +7
Model-based planning is often thought to be necessary for deep, careful reasoning and generalization in artificial agents. While recent successes of model-based reinforcement learn…